{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Semantic Segmentation and the Dataset\n",
    "\n",
    "On of the most important semantic segmentation dataset\n",
    "is [Pascal VOC2012](http://host.robots.ox.ac.uk/pascal/VOC/voc2012/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "origin_pos": 4,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading ../data/VOCtrainval_11-May-2012.tar from http://d2l-data.s3-accelerate.amazonaws.com/VOCtrainval_11-May-2012.tar...\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import os\n",
    "import torch\n",
    "import torchvision\n",
    "from d2l import torch as d2l\n",
    "\n",
    "d2l.DATA_HUB['voc2012'] = (d2l.DATA_URL + 'VOCtrainval_11-May-2012.tar',\n",
    "                           '4e443f8a2eca6b1dac8a6c57641b67dd40621a49')\n",
    "\n",
    "voc_dir = d2l.download_extract('voc2012', 'VOCdevkit/VOC2012')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Read all the input images and labels into the memory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "origin_pos": 7,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "def read_voc_images(voc_dir, is_train=True):\n",
    "    \"\"\"Read all VOC feature and label images.\"\"\"\n",
    "    txt_fname = os.path.join(voc_dir, 'ImageSets', 'Segmentation',\n",
    "                             'train.txt' if is_train else 'val.txt')\n",
    "    mode = torchvision.io.image.ImageReadMode.RGB\n",
    "    with open(txt_fname, 'r') as f:\n",
    "        images = f.read().split()\n",
    "    features, labels = [], []\n",
    "    for i, fname in enumerate(images):\n",
    "        features.append(torchvision.io.read_image(os.path.join(\n",
    "            voc_dir, 'JPEGImages', f'{fname}.jpg')))\n",
    "        labels.append(torchvision.io.read_image(os.path.join(\n",
    "            voc_dir, 'SegmentationClass' ,f'{fname}.png'), mode))\n",
    "    return features, labels\n",
    "\n",
    "train_features, train_labels = read_voc_images(voc_dir, True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Draw the first five input images and their labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "origin_pos": 10,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x216 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "n = 5\n",
    "imgs = train_features[0:n] + train_labels[0:n]\n",
    "imgs = [img.permute(1,2,0) for img in imgs]\n",
    "d2l.show_images(imgs, 2, n);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Enumerate\n",
    "the RGB color values and class names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "origin_pos": 12,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "VOC_COLORMAP = [[0, 0, 0], [128, 0, 0], [0, 128, 0], [128, 128, 0],\n",
    "                [0, 0, 128], [128, 0, 128], [0, 128, 128], [128, 128, 128],\n",
    "                [64, 0, 0], [192, 0, 0], [64, 128, 0], [192, 128, 0],\n",
    "                [64, 0, 128], [192, 0, 128], [64, 128, 128], [192, 128, 128],\n",
    "                [0, 64, 0], [128, 64, 0], [0, 192, 0], [128, 192, 0],\n",
    "                [0, 64, 128]]\n",
    "\n",
    "VOC_CLASSES = ['background', 'aeroplane', 'bicycle', 'bird', 'boat',\n",
    "               'bottle', 'bus', 'car', 'cat', 'chair', 'cow',\n",
    "               'diningtable', 'dog', 'horse', 'motorbike', 'person',\n",
    "               'potted plant', 'sheep', 'sofa', 'train', 'tv/monitor']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Find the class index for each pixel in a label"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "origin_pos": 15,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "def voc_colormap2label():\n",
    "    \"\"\"Build the mapping from RGB to class indices for VOC labels.\"\"\"\n",
    "    colormap2label = torch.zeros(256 ** 3, dtype=torch.long)\n",
    "    for i, colormap in enumerate(VOC_COLORMAP):\n",
    "        colormap2label[\n",
    "            (colormap[0] * 256 + colormap[1]) * 256 + colormap[2]] = i\n",
    "    return colormap2label\n",
    "\n",
    "def voc_label_indices(colormap, colormap2label):\n",
    "    \"\"\"Map any RGB values in VOC labels to their class indices.\"\"\"\n",
    "    colormap = colormap.permute(1, 2, 0).numpy().astype('int32')\n",
    "    idx = ((colormap[:, :, 0] * 256 + colormap[:, :, 1]) * 256\n",
    "           + colormap[:, :, 2])\n",
    "    return colormap2label[idx]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "For example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "origin_pos": 17,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(tensor([[0, 0, 0, 0, 0, 0, 0, 0, 0, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 0, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 1, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 0, 0, 1, 1]]),\n",
       " 'aeroplane')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = voc_label_indices(train_labels[0], voc_colormap2label())\n",
    "y[105:115, 130:140], VOC_CLASSES[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Using random cropping from image augmentation, we crop the same area of\n",
    "the input image and the label"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "origin_pos": 22,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x216 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def voc_rand_crop(feature, label, height, width):\n",
    "    \"\"\"Randomly crop both feature and label images.\"\"\"\n",
    "    rect = torchvision.transforms.RandomCrop.get_params(\n",
    "        feature, (height, width))\n",
    "    feature = torchvision.transforms.functional.crop(feature, *rect)\n",
    "    label = torchvision.transforms.functional.crop(label, *rect)\n",
    "    return feature, label\n",
    "\n",
    "imgs = []\n",
    "for _ in range(n):\n",
    "    imgs += voc_rand_crop(train_features[0], train_labels[0], 200, 300)\n",
    "\n",
    "imgs = [img.permute(1, 2, 0) for img in imgs]\n",
    "d2l.show_images(imgs[::2] + imgs[1::2], 2, n);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Custom Semantic Segmentation Dataset Class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "origin_pos": 25,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "class VOCSegDataset(torch.utils.data.Dataset):\n",
    "    \"\"\"A customized dataset to load the VOC dataset.\"\"\"\n",
    "\n",
    "    def __init__(self, is_train, crop_size, voc_dir):\n",
    "        self.transform = torchvision.transforms.Normalize(\n",
    "            mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])\n",
    "        self.crop_size = crop_size\n",
    "        features, labels = read_voc_images(voc_dir, is_train=is_train)\n",
    "        self.features = [self.normalize_image(feature)\n",
    "                         for feature in self.filter(features)]\n",
    "        self.labels = self.filter(labels)\n",
    "        self.colormap2label = voc_colormap2label()\n",
    "        print('read ' + str(len(self.features)) + ' examples')\n",
    "\n",
    "    def normalize_image(self, img):\n",
    "        return self.transform(img.float())\n",
    "\n",
    "    def filter(self, imgs):\n",
    "        return [img for img in imgs if (\n",
    "            img.shape[1] >= self.crop_size[0] and\n",
    "            img.shape[2] >= self.crop_size[1])]\n",
    "\n",
    "    def __getitem__(self, idx):\n",
    "        feature, label = voc_rand_crop(self.features[idx], self.labels[idx],\n",
    "                                       *self.crop_size)\n",
    "        return (feature, voc_label_indices(label, self.colormap2label))\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.features)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Reading the Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "origin_pos": 27,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "read 1114 examples\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "read 1078 examples\n"
     ]
    }
   ],
   "source": [
    "crop_size = (320, 480)\n",
    "voc_train = VOCSegDataset(True, crop_size, voc_dir)\n",
    "voc_test = VOCSegDataset(False, crop_size, voc_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "origin_pos": 30,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([64, 3, 320, 480])\n",
      "torch.Size([64, 320, 480])\n"
     ]
    }
   ],
   "source": [
    "batch_size = 64\n",
    "train_iter = torch.utils.data.DataLoader(voc_train, batch_size, shuffle=True,\n",
    "                                    drop_last=True,\n",
    "                                    num_workers=d2l.get_dataloader_workers())\n",
    "for X, Y in train_iter:\n",
    "    print(X.shape)\n",
    "    print(Y.shape)\n",
    "    break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Putting All Things Together"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "origin_pos": 33,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "def load_data_voc(batch_size, crop_size):\n",
    "    \"\"\"Load the VOC semantic segmentation dataset.\"\"\"\n",
    "    voc_dir = d2l.download_extract('voc2012', os.path.join(\n",
    "        'VOCdevkit', 'VOC2012'))\n",
    "    num_workers = d2l.get_dataloader_workers()\n",
    "    train_iter = torch.utils.data.DataLoader(\n",
    "        VOCSegDataset(True, crop_size, voc_dir), batch_size,\n",
    "        shuffle=True, drop_last=True, num_workers=num_workers)\n",
    "    test_iter = torch.utils.data.DataLoader(\n",
    "        VOCSegDataset(False, crop_size, voc_dir), batch_size,\n",
    "        drop_last=True, num_workers=num_workers)\n",
    "    return train_iter, test_iter"
   ]
  }
 ],
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   "name": "python"
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